{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([10.+10.j,  0. -2.j,  0. +0.j, -6. +0.j])"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_data=np.array([1.,2.,3.,4.,4.,3.,2.,1.])\n",
    "test_data.dtype=complex\n",
    "# test_data\n",
    "np.fft.fft(test_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x182a157ce88>]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "data = np.loadtxt('text.txt')\n",
    "data[:100]\n",
    "plt.plot(data[:100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\install\\Python37\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1333: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return np.asarray(x, float)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x182a1624088>]"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.fft.fft(data[:100])\n",
    "plt.plot(np.fft.fft(data[:100]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 23.-28.j,  -8. +2.j,  18.+30.j, -32.+13.j,  -5. -6.j,  23.-38.j,\n",
       "        -7. -9.j,  -4.+43.j,  25.-21.j, -13.-18.j,   5.+20.j, -29. +8.j,\n",
       "         0. +7.j,  22.-11.j, -10. -1.j, -20. -1.j,  27.-23.j,  16.+25.j,\n",
       "        -9. -9.j, -30.+11.j,   6.-17.j,  15.+16.j, -14. -1.j,  10. -8.j,\n",
       "       -12. -7.j,  11.+17.j, -10. -5.j,   4.-18.j,   2.+12.j,  -1.+11.j,\n",
       "        -9.-21.j,  15. +4.j,   6. +7.j, -35.+10.j,  12.-28.j,  15. +9.j,\n",
       "        24.-10.j, -22. +6.j, -25.+22.j,  -2. -4.j,   1.+19.j,  13.-39.j,\n",
       "        -4. +4.j,   9. -4.j,   4. +1.j,  -5.-14.j,   4.+29.j,   9. -3.j,\n",
       "       -39.-12.j,   5.+18.j])"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data1=data[:100]\n",
    "data1.dtype=complex\n",
    "data1\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "D:\\install\\Python37\\lib\\site-packages\\matplotlib\\cbook\\__init__.py:1333: ComplexWarning: Casting complex values to real discards the imaginary part\n",
      "  return np.asarray(x, float)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x182a169a588>]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "np.fft.fft(data1)\n",
    "plt.plot(np.fft.fft(data1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "import numpy as np\n",
    "x=np.array([1,2,3,4,5,6,7,8])\n",
    "win_coeffs=np.array([1,1,1,1])\n",
    "data = x.reshape(-1,2)\n",
    "data = np.flip(data,axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[2, 1],\n",
       "       [4, 3],\n",
       "       [6, 5],\n",
       "       [8, 7]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "data1 = data.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "data = np.array([1,2,3,4,5,6,7,8])\n",
    "channel_num = 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "disp_len = np.ceil(data.size / channel_num)\n",
    "patch_size = int(disp_len * channel_num - data.size)\n",
    "patch_data = np.concatenate((data, np.zeros(patch_size)))\n",
    "reshape_data = np.reshape(patch_data, (channel_num, -1), order='F')\n",
    "polyphase_data = np.flipud(reshape_data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1., 2., 3., 4., 5., 6., 7., 8., 0., 0.])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "patch_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[1., 6.],\n",
       "       [2., 7.],\n",
       "       [3., 8.],\n",
       "       [4., 0.],\n",
       "       [5., 0.]])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "reshape_data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[5., 0.],\n",
       "       [4., 0.],\n",
       "       [3., 8.],\n",
       "       [2., 7.],\n",
       "       [1., 6.]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "polyphase_data"
   ]
  }
 ],
 "metadata": {
  "interpreter": {
   "hash": "025ea33c0f928a4c0267c781cfd95d8c390c0ea0da6a24224ad21c94028fa66d"
  },
  "kernelspec": {
   "display_name": "Python 3.7.4 64-bit",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
